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Effects of repetitive Iodine Thyroid Blocking on the Fetal Brain and Thyroid in rats: a Systems Biology approach [Cortex]

ABSTRACT: Our group showed that repetitive dose of KI for eight days offers efficient protection against radiation exposure during nuclear accidents without toxic effects in adult rats. However, the effect of repetitive KI on the developing fetus still unknown especially on brain development, but a correlation between the impaired maternal thyroid status and a decrease in intelligence quotient has been observed. In this study, gene expression analysis of the progeny of repetitive KI-administered pregnant rats performed by our group showed distinct gene expression profile from two different organs: thyroid and cortex. To understand how these differentially expressed genes are implicated in the observed behaviour change, a systems biology approach was used to construct networks using three different techniques; Bayesian statistics using ShrinkNet, sPLS-DA on the DIABLO platform using mixOmics and manual construction of a Process Descriptive network. For each organ, we were able to construct gene expression network, to select genes that are most contributing to either control or KI-treated groups, respectively, and to construct the PD network from differentially expressed (DE) gene enriched with data from publications. Furthermore, we were able to connect DE genes from both organs into one network with genes from both organ participating in the same cellular processes that affect mitophagy and neuronal outgrowth.

ORGANISM(S): Rattus norvegicus

PROVIDER: GSE148280 | GEO | 2020/05/30

REPOSITORIES: GEO

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Project description:Introduction Iodine-131 (131I) is frequently used in nuclear medicine. Unbound or released 131I accumulate in the thyroid gland and may be detrimental to normal thyroid function. The aim of the present study was to identify biomarkers for 131I exposure in rat thyroid tissue and to assess the effect on thyroid function. Methods Thirty six male Sprague Dawley rats were i.v. injected with 150 Âµl saline solution containing 9.0, 88, 170, 260, 340, 760, 1300, or 4700 kBq (group A-H) 131I, or mock-treated with 150 Âµl saline solution only, and killed at 24 h after injection. Total RNA was extracted from individual thyroid tissue samples thyroids and mRNA levels were determined with the Agilent microarray platform. Results Estimated absorbed doses in treatment groups A-H was 0.0058, 0.057, 0.11, 0.17, 0.22, 0.5 Gy, 0.8 Gy, and 3 Gy. Totally, 429 transcripts were identified with a fold change fold change â¥ 1.5 and adjusted p-value â¤ 0.01. A trend with downregulation of thyroid hormone biosynthesis associated genes (e.g. thyroglobulin, thyroid peroxidase, the sodium-iodine symporter) was identified, but only statistically significant after 0.0058 and 0.22 Gy. Three transcripts coding for isoform 1 of the DBP protein showed a pattern with monotonous decrease in downregulation with absorbed dose between 0.0058-0.22 Gy. Changes in Dbp expression were not statistically significant between 0.5-3 Gy. However, a trend with downregulation at 0.5 and 0.8 Gy and upregulation and 3 Gy was identified. Previously, 131I (0.85-17 Gy) and 211At (0.023-32 Gy) exposure resulted in upregulation of Dbp in mice thyroid tissue 24 h after administrations. Additionally, a monotonous decrease in Dbp downregulation has been identified of in mouse kidney tissue at 8 and 12 months after 177Lu-octreotate administrations. Conclusion Conclusively, the Dbp gene is a promising candidate biomarker gene for exposure to 131I and possibly other internal radiation emitters. Further studies should be performed to establish how Dbp expression vary with dose-rate, absorbed dose, time after administration, different radiation qualities, and the function of Dbp. Total RNA was isolated from fresh-frozen individual thyroid tissue samples (Sprague Dawley rats). Each sample was run once. Four rats received the same treatment. Control samples (from non-irradiated rats) are included.

Project description:Uhlén2015 - Human tissue-based proteome metabolic network - thyroid Human thyroid tissue specific proteome metabolic network This model is described in the article: Tissue-based map of the human proteome Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson Å, Kampf C, Sjöstedt E, Asplund A, Olsson I, Edllund K, Lundberg E, Navani S, Szigyarto AC, Odeberg J, Djureinovic D, Takanen JO, Hober S, Alm T, Edqvist P, Berlin H, Tegel H, Mulder J, Rockberg J, Nilsson P, Schwenk JM, Hamsten M, von Feilitzen K, Forsberg M, Persson L, Johansson F, Zwahlen M, von Heijne G, Nielsen J, Pontén F. Science 2015 January; 347(6220) Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray–based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body. This model is hosted on BioModels Database and identified by: MODEL1411240008. To cite BioModels Database, please use: BioModels: ten-year anniversary . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Effects of repetitive Iodine Thyroid Blocking on the Fetal Brain and Thyroid in rats: a Systems Biology approach [Cortex]

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